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Descriptive Statistics (p. 38)
Describe participants behavior in a study. (Mean & Standard Deviation.)
Numbers that summarize and describe the behavior of participants in a study; the mean & standard deviation are descriptive statistics, for example.
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Effect Size (p. 50)
Strength of relationships between 2 or more variables.
The strength of the relationship between two or more variables, usually expressed as the proportion of variance in one variable that can be accounted for by another variable.
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Error Variance (p. 45)
Portion of total variance unaccounted for after systematic variance is removed.
Variance that is unrelated to variables in a study.
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Inferential Statistics
Mathematical analyses that allow researchers to draw conclusions regarding the reliability and generalizability of their data.
(T-tests and F-tests)
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Mean (p. 40)
The mathematical average of a set of scores.
The sum of a set of scored divided by the number of scores.
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Measures of Strenght of Association (p. 47)
Describes strength of relationship between variables.
(Effect size, Pearson correlation, & Multiple Correlation)
Descriptive statistics that convey information about the strength of the relationship between variables;
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Meta-analysis (p. 50)
Statistical procedure that analyzes and integrates results of many studies on a single topic.
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Range (p. 39)
A measure of variability that is equal to the difference between the largest & smallest scores in a set of data.
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Statistical Notation (p. 42)
A system of symbols that represents particular mathematical operations, variables, and statistics.
Example: x(bar) = mean, E = sum/add, and s^2 = variance.
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Systematic Variance (p. 43)
The portion of total variance that is related directly to variables being investigated.
The portion of the total variance in a set of scores that is related in an orderly, predictable fashion to the variables the researcher is investigating.
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Total Sum of Squares (p. 42)
The total variability in a set of data.
Calculated by subtracting the mean from each score, squaring the differences, and summing them.
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Total Variance (p. 43)
(The total sum of squares)/(# of scores) - (1)
The total sum of squares divided by the number of scores minus 1.
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Variability (p. 36)
The degree to which scores differ.
The degree to which scores in a set of data differ or vary from one another.
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Variance (p. 39)
The variability in a set of data.
A numerical index of the variability in a set of data.
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